Video surveillance networks with hundreds or thousands of cameras/sensors are deployed in various places. Such networks typically require complex video compression at each camera/sensor, a reliable communication network between the cameras/sensors and a control center for transmitting the compressed video to the control center, and matching video decompression at the control center.
One existing solution is to equip each video camera/sensor with high efficiency video coders, such as H.264 or H.265, and transmit the compressed video over a reliable network to a control center, where each video stream is decompressed and analyzed or displayed. Such video coders achieve high compression rates, but they are quite complex. In addition, the compressed signal is very sensitive to channel errors. Therefore, various communication techniques need to be applied to make the transmission reliable, for example, retransmission (as in transmission control protocol (TCP)) or forward error correction. These techniques add significant complexity and significantly reduce the available payload data rate, especially in low power transmission which results in low SNR in the received signal. Furthermore, if the channel quality varies, the communication protocol is often designed for the worst case, which can significantly further reduce the bit rate available for compressed video.
An alternative solution is to use compressive sensing (CS) instead of conventional video coding. CS is a signal compression technique with advantageous properties for video surveillance applications. According to CS, the compression operation is very simple and may be integrated with the video acquisition process, using a camera/sensor including, but not limited to, a lensless camera/sensor. It is possible to detect anomalies in the compressive sensing domain without actually decompressing the video, and it is possible to decompress only the elements of the regions of the video that are of interest, and in the decoding process it is possible to separate the moving object(s) from the background object(s).
However, implementation of CS requires a simple, robust and low power protocol for transmission of CS data from the camera/sensor to the control center.